import json import os from datetime import datetime, timezone from src.display.formatting import styled_error, styled_message, styled_warning from src.envs import API, EVAL_REQUESTS_PATH, TOKEN, QUEUE_REPO from src.submission.check_validity import ( already_submitted_models, check_model_card, get_model_size, ) REQUESTED_MODELS = None USERS_TO_SUBMISSION_DATES = None def add_new_eval( model: str, link: str, ): global REQUESTED_MODELS global USERS_TO_SUBMISSION_DATES if not REQUESTED_MODELS: REQUESTED_MODELS, USERS_TO_SUBMISSION_DATES = already_submitted_models(EVAL_REQUESTS_PATH) user_name = "" model_path = model if model_path.startswith('https:'): return styled_error("Huggingface model should be referred to by its name, not by its URL") if "/" in model: user_name = model.split("/")[0] model_path = model.split("/")[1] current_time = datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ") revision = "main" # Is the model info correctly filled? try: model_info = API.model_info(repo_id=model, revision=revision) except Exception: return styled_error("Could not get your model information. Please fill it up properly.") model_size = get_model_size(model_info=model_info) # Were the model card and license filled? try: license = model_info.cardData["license"] except Exception: return styled_error("Please select a license for your model") modelcard_OK, error_msg = check_model_card(model) if not modelcard_OK: return styled_error(error_msg) # Seems good, creating the eval print("Adding new eval") eval_entry = { "model": model, "revision": revision, "link": link, "status": "PENDING", "submitted_time": current_time, "params": model_size, "license": license, "private": False, } # Check for duplicate submission if f"{model}_{revision}" in REQUESTED_MODELS: return styled_warning("This model has been already submitted.") print("Creating eval file") OUT_DIR = f"{EVAL_REQUESTS_PATH}/{user_name}" os.makedirs(OUT_DIR, exist_ok=True) out_path = f"{OUT_DIR}/{model_path}_eval_request_False.json" with open(out_path, "w") as f: f.write(json.dumps(eval_entry)) print("Uploading eval file") API.upload_file( path_or_fileobj=out_path, path_in_repo=out_path.split("eval-queue/")[1], repo_id=QUEUE_REPO, repo_type="dataset", commit_message=f"Add {model} to eval queue", ) # Remove the local file os.remove(out_path) return styled_message( "Your request has been submitted to the evaluation queue!\nPlease wait for up to an hour for the model to show in the PENDING list." )